Emerging tech in the enterprise: How to catch up to your “consumers”

Another large gulf emerged with AI/ML, with 75% of respondents expressing familiarity but just 35% saying their organization had deployed AI/ML technologies. The emergence of generative AI has created a wave of hype — and plenty of controversy — around AI. But CIOs and other leaders also must consider the risks of adopting the technology without proper governance of the data used to fuel AI/ML algorithms.

The democratization of AI in the form of publicly available tools, such as ChatGPT, creates additional concerns, as organizations must guard against the technology’s potential to generate false or inaccurate statements, or plagiarize works of art or writing protected by copyright. This latest example of “shadow IT,” in which employees bring unapproved technology into the workplace, could introduce a variety of security and other risks into the enterprise.

Rather than restricting access to technologies, putting the right governance and guardrails around it allows employees to experiment with it in a safe environment.

Benefits of emerging tech in the background

The contradiction between high awareness and low adoption of AI/ML and VR/AR could be more attributed to communication than technology-averse leadership teams. Many employees likely already are benefiting from some of these new technologies because, unbeknownst to them, they have been implemented in other technologies or operate in the background, away from the user interface.

Communication is important, but it’s also about better follow-through. You want to show the workforce how these technologies are being used to enhance employee experience and move the needle on the business.

Adoption of machine generated data - Data here, there and everywhere

Not every technology in the study had high employee awareness. One example is edge computing — the distribution of computer processing and the delivery of data closer to the user. Edge technology is all but invisible to the average user, yet essential as massive amounts of data are generated and need to be collected, stored and processed with minimal latency. There is a rapid adoption of edge computing among many organizations as part of what EY Consulting calls distributed cloud platforms.

Massive amounts of data that are exponentially larger than what we see today are going to be in constant motion. By the end of 2025, EY Consulting estimates that 70% to 80% of a company’s data sets will be generated at the edge, and 80% of that data will be machine generated.

Organizations are beginning to realize their data distribution models need to adapt to a new decentralized, distributed computing model where critical applications are going to be very different than what they are accustomed to today.

How to stay relevant with new technologies

History has rewarded those companies that invest proactively in emerging technologies and formalize how they approach innovation of new processes and business models. For example, organizations that had tested and deployed remote collaboration tools prior to the COVID-19 pandemic were far more prepared for the shutdowns that closed most offices in March 2020.

The advice to leaders who want to move past the perception that their organization is late to embrace emerging technologies is to ensure that the CIO gets in front of the board to explain the practical implications of technologies that are generating a lot of hype. Nine out of ten boards are probably discussing the implications of generative AI and what it means for their business. This is the first time many people are getting an advance peek into something that is fast approaching, and boards need an experienced technologist advising them on how these technologies can be used to reimagine the business.